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3740 Total Publications

Automated MRI-Based Deep Learning Model for Detection of Alzheimer’s Disease Process
Feng, W, Halm-Lutterodt, NV, Tang, H, Mecum, A, Mesregah, MK, Ma, Y, Li, H, Zhang, F, Wu, Z and Yao, E
2020; Journal International Journal of Neural Systems; vol. 30; no. 6; pp. 2050032;
Brain regions vulnerable and resistant to aging without Alzheimer's disease
Feng, XY, Guo, J, Sigmon, HC, Sloan, RP, Brickman, AM, Provenzano, FA, Small, SA and Alzheimers Dis Neuroimaging, I
2020; Journal Plos One; vol. 15; no. 7;
Estimating brain age based on a uniform healthy population with deep learning and structural magnetic resonance imaging
Feng, XY, Lipton, ZC, Yang, J, Small, SA, Provenzano, FA, Alzheimers Dis Neuroimaging, I and Australian Imaging Biomarkers, L
2020; Journal Neurobiology of Aging; vol. 91; pp. 15-25;
Progression of Alzheimer's Disease by Self-Reported Cancer History in the Alzheimer's Disease Neuroimaging Initiative
Fowler, ME, Triebel, KL, Cutter, GR, Schneider, LS, Kennedy, RE and Alzheimer's Dis Neuroimaging, I
2020; Journal Journal of Alzheimers Disease; vol. 76; no. 2; pp. 691-701;
Studying the Manifold Structure of Alzheimers Disease: A Deep Learning Approach Using Convolutional Autoencoders
Martinez-Murcia, FJ, Ortiz, A, Gorriz, JM, Ramirez, J and Castillo-Barnes, D
PMID: 31217131 ; 2020; Journal Ieee Journal of Biomedical and Health Informatics; vol. 24; no. 1; pp. 17-26;
Alzheimer's disease diagnosis from diffusion tensor images using convolutional neural networks
Marzban, EN, Eldeib, AM, Yassine, IA and Kadah, YM
PMCID:7092978 ; 2020; Journal PLoS One; vol. 15; no. 3; pp. e0230409;
Improved Risk Stratification for Progression from Mild Cognitive Impairment to Alzheimer's Disease with a Multi-Analytical Evaluation of Amyloid-β Positron Emission Tomography
Beyer, L, Brendel, M, Scheiwein, F, Sauerbeck, J, Hosakawa, C, Alberts, I, Shi, K, Bartenstein, P, Ishii, K, Seibyl, J, Cumming, P and Rominger, A
2020; Journal J Alzheimers Dis; vol. 74; no. 1; pp. 101-112;
Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models
Biffi, C, Doumou, G, Duan, J, Prasad, SK, Cook, SA, DP, OR, Rueckert, D, Cerrolaza, JJ, Tarroni, G, Bai, W, De Marvao, A, Oktay, O, Ledig, C, Le Folgoc, L and Kamnitsas, K
2020; Journal IEEE Trans Med Imaging;
Estimation of connectional brain templates using selective multi-view network normalization
Dhifallah, S, Rekik, I and Alzheimer's Dis, N
2020; Journal Medical Image Analysis; vol. 59;